Towards Energy-Efficient Indoor Environment Quality using Artificial Intelligence: A Bibliometric Analysis

With the increasing awareness of sustainability in the built environment, there is a pressing need to achieve a comfortable and healthy indoor environment with optimized energy consumption. In this context, artificial intelligence (AI) has shown its potential as a tool for energy optimization while upholding high IEQ standards. This research paper explores the current and future research trends in utilizing AI to achieve an energy-efficient indoor environment quality (IEQ). Bibliometric analysis is used as a methodology to identify key research themes and the thematic evolution of a research field. Based on a carefully formulated search term, a case study is performed using bibliometric data downloaded from the SCOPUS database. Upon data pre-processing steps, the research evolution of the field is presented visually using strategic mapping and thematic evolution networks over the years 2018-2023, with discovered insights discussed. Finally, some discussion on future works is given based on key insights.

Authors

Institutions

Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/ieem62345.2024.10857153
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards Energy-Efficient Indoor Environment Quality using Artificial Intelligence: A Bibliometric Analysis

M. F. Lee, Boon Tuan Tee, Soon Chong Johnson Lim, Peter Siew
Building Energy and Comfort Optimization
article

Towards Energy-Efficient Indoor Environment Quality using Artificial Intelligence: A Bibliometric Analysis

M. F. Lee, Boon Tuan Tee, Soon Chong Johnson Lim, Peter Siew
article en

Abstract

With the increasing awareness of sustainability in the built environment, there is a pressing need to achieve a comfortable and healthy indoor environment with optimized energy consumption. In this context, artificial intelligence (AI) has shown its potential as a tool for energy optimization while upholding high IEQ standards. This research paper explores the current and future research trends in utilizing AI to achieve an energy-efficient indoor environment quality (IEQ). Bibliometric analysis is used as a methodology to identify key research themes and the thematic evolution of a research field. Based on a carefully formulated search term, a case study is performed using bibliometric data downloaded from the SCOPUS database. Upon data pre-processing steps, the research evolution of the field is presented visually using strategic mapping and thematic evolution networks over the years 2018-2023, with discovered insights discussed. Finally, some discussion on future works is given based on key insights.

Technical University of Malaysia Malacca (MY), Universiti Teknologi MARA (MY), Tun Hussein Onn University of Malaysia (MY)
Universiti Tun Hussein Onn Malaysia
Openalex Percentile: Top 71%
Building Energy and Comfort Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Towards Energy-Efficient Indoor Environment Quality using Artificial Intelligence: A Bibliometric Analysis — M. F. Lee, Boon Tuan Tee, et al. · (2024) | TGRS Research Map | TGRS